9 citations · 15 across the 3 of their papers we have counts for
3 papers
cs.LG2020★ 1 cited
Interventional Domain Adaptation
Jun Wen, Changjian Shui, Kun Kuang +4
Domain adaptation (DA) aims to transfer discriminative features learned from source domain to target domain. Most of DA methods focus on enhancing feature transferability through d…
cs.LG2019★ 9 cited
Bayesian Uncertainty Matching for Unsupervised Domain Adaptation
Jun Wen, Nenggan Zheng, Junsong Yuan +2
Domain adaptation is an important technique to alleviate performance degradation caused by domain shift, e.g., when training and test data come from different domains. Most existin…
cs.LG2018★ 5 cited
Exploiting Local Feature Patterns for Unsupervised Domain Adaptation
Jun Wen, Risheng Liu, Nenggan Zheng +3
Unsupervised domain adaptation methods aim to alleviate performance degradation caused by domain-shift by learning domain-invariant representations. Existing deep domain adaptation…